On Adaptive Attacks to Adversarial Example Defenses

19 February 2020

Wieland Brendel

Papers citing "On Adaptive Attacks to Adversarial Example Defenses"

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Pruning in the Face of Adversaries F. Merkle Maximilian Samsinger Pascal Schöttle AAML CVBM 9 3 0 19 Aug 2021
Robustness testing of AI systems: A case study for traffic sign recognition Christian Berghoff Pavol Bielik Matthias Neu Petar Tsankov Arndt von Twickel AAML 6 13 0 13 Aug 2021
Neural Network Repair with Reachability Analysis Xiaodong Yang Tomochika Yamaguchi Hoang-Dung Tran Bardh Hoxha Taylor T. Johnson Danil Prokhorov AAML 17 29 0 09 Aug 2021
Poison Ink: Robust and Invisible Backdoor Attack Jie M. Zhang Dongdong Chen Qidong Huang Jing Liao Weiming Zhang Huamin Feng G. Hua Nenghai Yu AAML 17 84 0 05 Aug 2021
On the Exploitability of Audio Machine Learning Pipelines to Surreptitious Adversarial Examples Adelin Travers Lorna Licollari Guanghan Wang Varun Chandrasekaran Adam Dziedzic David Lie Nicolas Papernot AAML 15 3 0 03 Aug 2021
Advances in adversarial attacks and defenses in computer vision: A survey Naveed Akhtar Ajmal Saeed Mian Navid Kardan M. Shah AAML 22 234 0 01 Aug 2021
Detecting Adversarial Examples Is (Nearly) As Hard As Classifying Them Florian Tramèr AAML 14 64 0 24 Jul 2021
On the Certified Robustness for Ensemble Models and Beyond Zhuolin Yang Linyi Li Xiaojun Xu B. Kailkhura Tao Xie Bo-wen Li AAML 11 47 0 22 Jul 2021
Responsible and Regulatory Conform Machine Learning for Medicine: A Survey of Challenges and Solutions Eike Petersen Yannik Potdevin Esfandiar Mohammadi Stephan Zidowitz Sabrina Breyer ... Sandra Henn Ludwig Pechmann M. Leucker P. Rostalski Christian Herzog FaML AILaw OOD 14 21 0 20 Jul 2021
AID-Purifier: A Light Auxiliary Network for Boosting Adversarial Defense Duhun Hwang Eunjung Lee Wonjong Rhee AAML 156 14 0 14 Jul 2021
Detect and Defense Against Adversarial Examples in Deep Learning using Natural Scene Statistics and Adaptive Denoising Anouar Kherchouche Sid Ahmed Fezza W. Hamidouche AAML 17 9 0 12 Jul 2021
Adversarial for Good? How the Adversarial ML Community's Values Impede Socially Beneficial Uses of Attacks Kendra Albert Maggie K. Delano B. Kulynych Ramnath Kumar AAML 12 4 0 11 Jul 2021
GGT: Graph-Guided Testing for Adversarial Sample Detection of Deep Neural Network Zuohui Chen Renxuan Wang Jingyang Xiang Yue Yu Xin Xia S. Ji Qi Xuan Xiaoniu Yang 21 1 0 09 Jul 2021
Universal 3-Dimensional Perturbations for Black-Box Attacks on Video Recognition Systems Shangyu Xie Han Wang Yu Kong Yuan Hong AAML 11 25 0 09 Jul 2021
Understanding Intrinsic Robustness Using Label Uncertainty Xiao Zhang David E. Evans OOD 25 5 0 07 Jul 2021
On Robustness of Lane Detection Models to Physical-World Adversarial Attacks in Autonomous Driving Takami Sato Qi Alfred Chen AAML ELM 20 6 0 06 Jul 2021
GradDiv: Adversarial Robustness of Randomized Neural Networks via Gradient Diversity Regularization Sungyoon Lee Hoki Kim Jaewook Lee AAML 16 52 0 06 Jul 2021
Evading Adversarial Example Detection Defenses with Orthogonal Projected Gradient Descent Oliver Bryniarski Nabeel Hingun Pedro Pachuca Vincent Wang Nicholas Carlini AAML 17 34 0 28 Jun 2021
Data Poisoning Won't Save You From Facial Recognition Evani Radiya-Dixit Sanghyun Hong Nicholas Carlini Florian Tramèr AAML PICV 13 56 0 28 Jun 2021
Who is Responsible for Adversarial Defense? Kishor Datta Gupta D. Dasgupta AAML 17 2 0 27 Jun 2021
Reachability Analysis of Convolutional Neural Networks Xiaodong Yang Tomoya Yamaguchi Hoang-Dung Tran Bardh Hoxha Taylor T. Johnson Danil Prokhorov FAtt 6 5 0 22 Jun 2021
NCIS: Neural Contextual Iterative Smoothing for Purifying Adversarial Perturbations Sungmin Cha Naeun Ko Young Joon Yoo Taesup Moon AAML 13 2 0 22 Jun 2021
Delving into the pixels of adversarial samples Blerta Lindqvist AAML 9 0 0 21 Jun 2021
Group-Structured Adversarial Training Farzan Farnia Amirali Aghazadeh James Y. Zou David Tse AAML 11 0 0 18 Jun 2021
Indicators of Attack Failure: Debugging and Improving Optimization of Adversarial Examples Maura Pintor Luca Demetrio Angelo Sotgiu Ambra Demontis Nicholas Carlini Battista Biggio Fabio Roli AAML 21 28 0 18 Jun 2021
Adversarial Visual Robustness by Causal Intervention Kaihua Tang Ming Tao Hanwang Zhang CML AAML 11 21 0 17 Jun 2021
Real-time Adversarial Perturbations against Deep Reinforcement Learning Policies: Attacks and Defenses Buse G. A. Tekgul Shelly Wang Samuel Marchal Nadarajah Asokan AAML OffRL 10 5 0 16 Jun 2021
Towards Adversarial Robustness via Transductive Learning Jiefeng Chen Yang Guo Xi Wu Tianqi Li Qicheng Lao Yingyu Liang S. Jha AAML 10 5 0 15 Jun 2021
Voting for the right answer: Adversarial defense for speaker verification Haibin Wu Yang Zhang Zhiyong Wu Dong Wang Hung-yi Lee AAML 23 25 0 15 Jun 2021
Selection of Source Images Heavily Influences the Effectiveness of Adversarial Attacks Utku Ozbulak Esla Timothy Anzaku W. D. Neve Arnout Van Messem AAML 20 10 0 14 Jun 2021
Boosting Randomized Smoothing with Variance Reduced Classifiers Miklós Z. Horváth Mark Niklas Muller Marc Fischer Martin Vechev AAML UQCV 11 48 0 13 Jun 2021
ATRAS: Adversarially Trained Robust Architecture Search Yigit Can Alparslan Edward J. Kim OOD AAML 13 1 0 13 Jun 2021
CARTL: Cooperative Adversarially-Robust Transfer Learning Dian Chen Hongxin Hu Qian Wang Yinli Li Cong Wang Chao Shen Qi Li 15 13 0 12 Jun 2021
CausalAdv: Adversarial Robustness through the Lens of Causality Yonggang Zhang Mingming Gong Tongliang Liu Gang Niu Xinmei Tian Bo Han Bernhard Schölkopf Kun Zhang OOD AAML CML 17 35 0 11 Jun 2021
Adversarial purification with Score-based generative models Jongmin Yoon S. Hwang Juho Lee DiffM 14 150 0 11 Jun 2021
An Ensemble Approach Towards Adversarial Robustness Haifeng Qian AAML UQCV 6 0 0 10 Jun 2021
Improving White-box Robustness of Pre-processing Defenses via Joint Adversarial Training Dawei Zhou N. Wang Xinbo Gao Bo Han Jun Yu Xiaoyu Wang Tongliang Liu AAML 13 4 0 10 Jun 2021
HASI: Hardware-Accelerated Stochastic Inference, A Defense Against Adversarial Machine Learning Attacks Mohammad Hossein Samavatian Saikat Majumdar Kristin Barber R. Teodorescu AAML 10 4 0 09 Jun 2021
Taxonomy of Machine Learning Safety: A Survey and Primer Sina Mohseni Haotao Wang Zhiding Yu Chaowei Xiao Zhangyang Wang J. Yadawa 17 31 0 09 Jun 2021
Adversarial Attack and Defense in Deep Ranking Mo Zhou Le Wang Zhenxing Niu Qilin Zhang N. Zheng G. Hua OOD 12 13 0 07 Jun 2021
Two Coupled Rejection Metrics Can Tell Adversarial Examples Apart Tianyu Pang Huishuai Zhang Di He Yinpeng Dong Hang Su Wei Chen Jun Zhu Tie-Yan Liu AAML 6 16 0 31 May 2021
$Robustifying $\ell_\infty$ Adversarial Training to the Union of Perturbation Models$ Robustifying $\ell_\infty$ Adversarial Training to the Union of Perturbation Models Ameya D. Patil Michael Tuttle A. Schwing Naresh R Shanbhag AAML 21 0 0 31 May 2021
Adversarial Robustness against Multiple and Single $l_p$ -Threat Models via Quick Fine-Tuning of Robust Classifiers Francesco Croce Matthias Hein OOD AAML 20 18 0 26 May 2021
Deep Repulsive Prototypes for Adversarial Robustness A. Serban E. Poll Joost Visser OOD 11 3 0 26 May 2021
Exploring Misclassifications of Robust Neural Networks to Enhance Adversarial Attacks Leo Schwinn René Raab A. Nguyen Dario Zanca Bjoern M. Eskofier AAML 6 56 0 21 May 2021
Fighting Gradients with Gradients: Dynamic Defenses against Adversarial Attacks Dequan Wang An Ju Evan Shelhamer David A. Wagner Trevor Darrell AAML 18 26 0 18 May 2021
Automated Decision-based Adversarial Attacks Qi-An Fu Yinpeng Dong Hang Su Jun Zhu AAML 11 1 0 09 May 2021
Dynamic Defense Approach for Adversarial Robustness in Deep Neural Networks via Stochastic Ensemble Smoothed Model Ruoxi Qin Linyuan Wang Xing-yuan Chen Xuehui Du Bin Yan AAML 17 5 0 06 May 2021
BAARD: Blocking Adversarial Examples by Testing for Applicability, Reliability and Decidability Luke Chang Katharina Dost Kaiqi Zhao Ambra Demontis Fabio Roli Gillian Dobbie Jörg Simon Wicker AAML 11 2 0 02 May 2021
Random Noise Defense Against Query-Based Black-Box Attacks Zeyu Qin Yanbo Fan H. Zha Baoyuan Wu AAML 11 58 0 23 Apr 2021